Instructors: Francesco Delli Priscoli, Andrea Cristofaro
Course web page: www.diag.uniroma1.it/~oriolo/cams
Credits: 6
Infostud code: 1041427

Objectives

The course presents the basic methods for modeling, analyzing and controlling multi-agent systems, with special emphasis on distributed strategies. Applications will be presented in the control of communication, electrical and transport networks/systems, as well as of multi-robot systems. The student will be able to analyze and design architectures, algorithms, and modules for controlling multi-agent systems.

Program

Part I. Examples of multi-agent scenarios in communication, energy and transport networks/systems derived from research projects funded by the European Union. Comparison between centralized and distributed architectures. Extension of the methodologies (especially machine learning, reinforcement learning, model predictive control) and problems (concerning the control of communication, energy and transport networks/systems, as well as the security of such networks/systems) studied in the context of previous courses (in particular, Control of Communication and Energy Network) to the multi-agent context.
Part II. Introduction: Examples of application of multi-robot systems. Centralized vs. decentralized architectures. Mathematical tools: Adjacency graph and matrix; Laplacian; Connectivity and Consensus; Passivity and Lyapunov stability; Interconnection of mechanical systems. Application to multi-UAV systems: Formation control with time-varying topology; Formation control with connectivity maintenance; Steady-state behaviors; Bearing-based formation control. Application to multi-UGV systems: Cooperative exploration of unknown environments; Mutual localization with anonymous measurements; Target localization and encircling.

Type of exam: Evaluation of two projects (on Part I and Part II, respectively)

Reference texts

• M. Vidal, "Fundamentals of Multiagent Systems," 2011
• M. Mesbahi and M. Egerstedt, "Graph Theoretic Methods in Multiagent Systems," Princeton University Press, 2010